Robots have become an important part of our daily lives today. This article would primarily study how robotic navigation works and why it is so popular today. Today, robots have become a part of various industries such as space, transportation, defense, and many more. Mobile robots are also known to perform various functions such as managing a disaster and different emergency and rescue events. Robots are also used in platforms for exhaustive searches, for example, a system to search for patents and trademarks.
Robots need a safe and fluid environment to travel freely from the starting position to the main target. This safe journey is guaranteed by robotic navigation. There are several navigation techniques to guarantee this at a dynamic and static level. Robot navigation can be defined as the robot’s own ability to decide on a path and orientation within its “reference frame” to reach its goal. Three factors form the main basis for mobile navigation and obstacle avoidance: the first is autolocation; the second method is route planning. The last approach is the construction and interpretation of maps.
There are various navigation methods like Voronoi graph, grid lines, visibility graphs, “artificial potential field method”, etc. There are three broad categories of mobile browsing algorithms: the first and foremost is the deterministic algorithm, then comes the non-deterministic algorithm, and last on the list is the evolutionary algorithm. This is the general general classification of algorithms. Other forms of algorithms are also found under these three broad categories. Navigation is a very important task, and it can be global or local.
SLAM OR Simultaneous localization and mapping is a problem in calculus geometry that helps update maps. It was first investigated in detail in the year 1986. This also tracks one agent at a time. SLAM algorithms are popularly found in self-driving cars, rovers to control planetary motions, and various other robots. There are also different types of SLAM algorithms. “Collaborative SLAM” helps to form 3D images by combining images from more than one robot. There is also something known as “audiovisual SLAM” which was originally designed for human-robot interaction.
The ORB SLAM mono camera is one of the first real-time SLAM systems that is visual. This helps to study and visually train the maps for robot navigation and obstacle avoidance. Various search websites that use robots for their search algorithm also need robotic navigation. Optical vision is also used to see maps. Various computer algorithms and optical sensors are used for this.
Therefore, it can be concluded that since robots are an important part of our lives, robotic navigation and obstacle avoidance are also very essential. that’s because robots need to navigate freely in their environment.